Adaptive slice-specific z-shimming for 2D spoiled gradient-echo sequences

An Improved Postprocessing Method to Mitigate the Macroscopic Cross-Slice B0 Field Effect on R2* Measurements in the Mouse Brain at 7T

The MR transverse relaxation rate, R2*, has been widely used to detect iron and myelin content in tissue. However, it is also sensitive to macroscopic B0 inhomogeneities. One approach to correct for the B0 effect is to fit gradient-echo signals with the three-parameter model, a sinc function-weighted monoexponential decay. However, such three-parameter models are subject to increased noise sensitivity. To address this issue, this study presents a two-stage fitting procedure based on the three-parameter model to mitigate the B0 effect and reduce the noise sensitivity of R2* measurement in the mouse brain at 7T. MRI scans were performed on eight healthy mice. The gradient-echo signals were fitted with the two-stage fitting procedure to generate R2corr_t*. The signals were also fitted with the monoexponential and three-parameter models to generate R2nocorr* and R2corr*, respectively. Regions of interest (ROIs), including the corpus callosum, internal capsule, somatosensory cortex, caudo-putamen, thalamus, and lateral ventricle, were selected to evaluate the within-ROI mean and standard deviation (SD) of the R2* measurements. The results showed that the Akaike information criterion of the monoexponential model was significantly reduced by using the three-parameter model in the selected ROIs (p = 0.0039-0.0078). However, the within-ROI SD of R2corr* using the three-parameter model was significantly higher than that of the R2nocorr* in the internal capsule, caudo-putamen, and thalamus regions (p = 0.0039), a consequence partially due to the increased noise sensitivity of the three-parameter model. With the two-stage fitting procedure, the within-ROI SD of R2corr* was significantly reduced by 7.7-30.2% in all ROIs, except for the somatosensory cortex region with a fast in-plane variation of the B0 gradient field (p = 0.0039-0.0078). These results support the utilization of the two-stage fitting procedure to mitigate the B0 effect and reduce noise sensitivity for R2* measurement in the mouse brain.

Adaptive slice-specific z-shimming for 2D spoiled gradient-echo sequences

Purpose

To reduce the misbalance between compensation gradients and macroscopic field gradients, we introduce an adaptive slice‐specific z‐shimming approach for 2D spoiled multi‐echo gradient‐echoe sequences in combination with modeling of the signal decay.

Methods

Macroscopic field gradients were estimated for each slice from a fast prescan (15 seconds) and then used to calculate slice‐specific compensation moments along the echo train. The coverage of the compensated field gradients was increased by applying three positive and three negative moments. With a forward model, which considered the effect of the slice profile, the z‐shim moment, and the field gradient, R2∗ maps were estimated. The method was evaluated in phantom and in vivo measurements at 3 T and compared with a spoiled multi‐echo gradient‐echo and a global z‐shimming approach without slice‐specific compensation.

Results

The proposed method yielded higher SNR in R2∗ maps due to a broader range of compensated macroscopic field gradients compared with global z‐shimming. In global white matter, the mean interquartile range, proxy for SNR, could be decreased to 3.06 s⁻¹ with the proposed approach, compared with 3.37 s⁻¹ for global z‐shimming and 3.52 s⁻¹ for uncompensated multi‐echo gradient‐echo.

Conclusion

Adaptive slice‐specific compensation gradients between echoes substantially improved the SNR of R2∗ maps, and the signal could also be rephased in anatomical areas, where it has already been completely dephased.